Sanction teardown · First-tier Tribunal (Property Chamber), UK · 2026-04-13
Brook House (Henley) RTM Company Limited v Henley Brook Limited
What happened
In First-tier Tribunal (Property Chamber), UK, a filing relied on an unnamed/unconfirmed AI tool to help draft legal argument. The court identified the following problems with the citations in that filing:
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Fabricated (Case Law)The Respondent relied on a purported paragraph 28 of Gala Unity, but the Tribunal noted that the judgment extends only to paragraph 19 and contains no such paragraph.
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False Quotes (Case Law)The Respondent relied on paragraph 41 of FirstPort for a proposition about appurtenant property and service of the claim notice, but the Tribunal found that paragraph 41 contained no relevant supporting content.
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Misrepresented (Legal Norm)The counter-notice attributed a 25% non-residential internal-floor-area test to section 72(1)(b), but the Tribunal found that provision did not say this and identified section 72(6) and Schedule 6 as the relevant statutory route.
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Misrepresented (Legal Norm)The Respondent treated external car-park and access areas as part of the functional premises for the internal-floor-area calculation, producing an asserted 52.68% non-residential proportion. The Tribunal found those areas had no internal floor area and had to be disregarded.
Which AI tool
an unnamed/unconfirmed AI tool. Note: Charlotin's public database records tool attribution only where a court order, brief, or reporting on the matter states it explicitly; "unidentified" or "implied" means the record indicates AI use but does not name a specific product — we do not guess.
Outcome
Not specified in source record.
How Citation Safe would have caught this
Citation Safe runs three deterministic layers before a brief is filed: (1) does the citation exist against CourtListener's database of published opinions, (2) if quoted, does that exact language appear in the source, (3) does the cited case actually support the proposition it is cited for. Fabricated case citations fail Layer 1. Fabricated or misattributed quotations fail Layer 2 even when the underlying case is real. Misrepresented holdings — a real case cited for a proposition it does not support — are the target of Layer 3. None of these checks involve asking another language model whether the citation looks right; they are lookups and text-matches against the actual source, which is why a hallucinated citation has to survive a direct lookup against the authoritative source — not another model's opinion — to earn a VERIFIED stamp; our measured false-verify rate is published live at /quality.
Check a brief before you file it → · See our live false-verify rate
Source: https://naturalandartificiallaw.com/76-uk-cases-of-ai-hallucinated-false-citations/, via Damien Charlotin's public AI Hallucination Cases Database (CC0).